






'''simple docstring'''




def    __lowercase		(     __lowercase			)			->		Dict:

      '''simple docstring'''


      _A     	=      [0] * len(__lowercase			)

      for i in range(1  ,    len(__lowercase			)			):
            # use last results for better performance - dynamic programming
            _A     	=      prefix_result[i - 1]
            while j > 0 and input_string[i] != input_string[j]:
                  _A     	=      prefix_result[j - 1]

            if input_string[i] == input_string[j]:
                  j += 1
            _A     	=      j

      return prefix_result

def    __lowercase		(     __lowercase			)			->		Dict:

      '''simple docstring'''


      return max(prefix_function(__lowercase			)			)


if __name__ == "__main__":
    import doctest

    doctest.testmod()






"""simple docstring"""



from typing import Union

import fire
import torch
from tqdm import tqdm



def 	_lowerCamelCase(	a   ,    a = "cpu"   ,    a = None				):
       __a       =    torch.load(a   ,    map_location=a				)
       for k, v in tqdm(state_dict.items()				):
              if not isinstance(a   ,    torch.Tensor				):
                     raise TypeError("FP16 conversion only works on paths that are saved state dicts, like pytorch_model.bin"				)
              __a       =    v.half()
       if save_path is None:  # overwrite src_path
              __a       =    src_path
       torch.save(a   ,    a				)


if __name__ == "__main__":
   fire.Fire(convert)
